Towards characterization of actor evolution and interactions in news corpora
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Connecting the dots between news articles
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Trains of thought: generating information maps
Proceedings of the 21st international conference on World Wide Web
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Providing the history and context(s) of a news article that emerges in the middle of an evolving news story--sometimes multiple news stories--is a complex task. The complexity of the task is compounded by the fact that different users are interested in different contexts of the article, and it is impossible to guess what a particular user is most interested in. In this paper, we introduce ESTHETE, a system that provides rich context(s) (through what we call personalized flexible context extraction), by preprocessing and storing articles in a structured representation (directed graphs) that makes it easy for the user to explore different contexts. The advantage of this approach is that the incremental computational expense in incorporating new articles as they are published is minimal. Our system is available at: http://konfrap.com/esthete.